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Association of insomnia and daytime sleepiness with low back pain: A bidirectional mendelian randomization analysis

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Purpose: Observational research has indicated the presence of a causal relationship between sleep disturbances and low back pain (LBP). However, the link may have been biased by confounding factors. The purpose of this study was to examine the potential causal association of insomnia and daytime sleepiness with LBP by using mendelian randomization (MR).Methods: Genome-wide association study (GWAS) summary statistics of insomnia were obtained from a large-scale GWAS meta-analysis (n = 1,331,010; individuals from UK Biobank and 23andMe) or UK Biobank alone (n = 453,379). The summary statistics of daytime sleepiness were from UK Biobank (n = 452,071) and LBP were provided by the FinnGen Release 6 (210,645 individuals with 16,356 LBP cases and 194,289 controls) or UK Biobank (5,423 cases versus 355,771 controls). Linkage disequilibrium score (LDSC) regression and bidirectional MR analysis was employed to estimate genetic correlation and causal relationship. In the MR analysis, the inverse variance weighted method (IVW) was utilized as the main analysis procedure, while MR-Egger, Weighted median and Robust adjusted profile score (RAPS) were utilized for supplementary analyses.Results: LDSC analysis showed that LBP were significantly genetically correlated with insomnia (rg = 0.57, p = 2.26e-25) and daytime sleepiness (rg = 0.18, p = 0.001). The MR analysis revealed that genetically predicted insomnia was significantly associated with an increased risk of LBP (OR = 1.250, 95% CI: 1.186–1.318; p = 1.69e-16). However, the reverse causality was not confirmed. No evidence was identified supporting causality of daytime sleepiness and LBP.Conclusion: This study demonstrates a putative causal link of insomnia on LBP and a null causal effect of LBP on insomnia. Furthermore, a causal link between daytime sleepiness and LBP were not reported. This finding may stimulate new strategies for patient management in clinical practice, benefiting public health.
Title: Association of insomnia and daytime sleepiness with low back pain: A bidirectional mendelian randomization analysis
Description:
Purpose: Observational research has indicated the presence of a causal relationship between sleep disturbances and low back pain (LBP).
However, the link may have been biased by confounding factors.
The purpose of this study was to examine the potential causal association of insomnia and daytime sleepiness with LBP by using mendelian randomization (MR).
Methods: Genome-wide association study (GWAS) summary statistics of insomnia were obtained from a large-scale GWAS meta-analysis (n = 1,331,010; individuals from UK Biobank and 23andMe) or UK Biobank alone (n = 453,379).
The summary statistics of daytime sleepiness were from UK Biobank (n = 452,071) and LBP were provided by the FinnGen Release 6 (210,645 individuals with 16,356 LBP cases and 194,289 controls) or UK Biobank (5,423 cases versus 355,771 controls).
Linkage disequilibrium score (LDSC) regression and bidirectional MR analysis was employed to estimate genetic correlation and causal relationship.
In the MR analysis, the inverse variance weighted method (IVW) was utilized as the main analysis procedure, while MR-Egger, Weighted median and Robust adjusted profile score (RAPS) were utilized for supplementary analyses.
Results: LDSC analysis showed that LBP were significantly genetically correlated with insomnia (rg = 0.
57, p = 2.
26e-25) and daytime sleepiness (rg = 0.
18, p = 0.
001).
The MR analysis revealed that genetically predicted insomnia was significantly associated with an increased risk of LBP (OR = 1.
250, 95% CI: 1.
186–1.
318; p = 1.
69e-16).
However, the reverse causality was not confirmed.
No evidence was identified supporting causality of daytime sleepiness and LBP.
Conclusion: This study demonstrates a putative causal link of insomnia on LBP and a null causal effect of LBP on insomnia.
Furthermore, a causal link between daytime sleepiness and LBP were not reported.
This finding may stimulate new strategies for patient management in clinical practice, benefiting public health.

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